Magnetic properties and charge transport mechanisms in oxygen-deficient HfxZr1-xO2-y nanoparticles
Abstract
Study of nanoscale hafnia-zirconia physical properties is the key topic in fundamental and applied science. However, charge transport mechanisms and magnetic properties of hafnia-zirconia nanoparticles are very poorly studied both theoretically and experimentally. In this work we observed a superparamagnetic-like and superparaelectric-like response of ultra-small hafnia-zirconia nanoparticles prepared by the solid-state organonitrate synthesis. The EPR spectra of hafnia-zirconia nanopowders reveal the presence of paramagnetic defect centers, which may be hafnium and/or zirconium ions, which trapped an electron near an oxygen vacancy and changed their valence state from the non-paramagnetic +4 to the paramagnetic +3 state. The Raman spectra indicate the decisive role of surface defects, presumably oxygen vacancies, for all studied Zr compositions.At the same time the EELS analysis does not reveal any noticeable concentration of magnetic impurities in the hafnia-zirconia nanopowders, and the X-ray diffraction analysis reveals the dominant presence of the orthorhombic phase. We observed that the quasi-static relative dielectric permittivity of the hafnia-zirconia nanopowders overcomes 106 - 107 and related the colossal values with the superparaelectric state of the nanoparticles cores induced by the flexo-electro-chemical strains. It has been found that ultra-small hafnia-zirconia nanoparticles reveal posistor effect and relatively large values of accumulated charge. Thus, obtained results open the way for creation of silicon-compatible ferroics oxygen-deficient hafnia-zirconia nanoparticles with superparamagnetic and superparaelectric properties, which may be used in advanced FETs and electronic logic elements.
Turn this paper into a full lesson
ArcXiv compiles a staged curriculum from this paper: 8-12 lessons across beginner → advanced, synthesised section guides, visuals, flashcards, a quiz, exercises, and on-demand deep dives per section. Grounded in the abstract, never invented.